ArticleBMC medical research methodology2012
Modeling gradually changing seasonal variation in count data using state space models: a cohort study of hospitalization rates of stroke in atrial fibrillation patients in Denmark from 1977 to 2011.
Article in BMC medical research methodology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Seasonality of tuberculosis in intermediate endemicity setting dominated by reactivation diseases in Hong Kong.Scientific reports · 2021Article
- Temperature and Precipitation Associate With Ischemic Stroke Outcomes in the United States.Journal of the American Heart Association · 2018Article
- Seasonal Variation in Paroxysmal Atrial Fibrillation: A Systematic Review.Journal of atrial fibrillationArticle
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5 authors.
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Abstract
backgroundSeasonal variation in the occurrence of cardiovascular diseases has been recognized for decades. In particular, incidence rates of hospitalization with atrial fibrillation (AF) and stroke have shown to exhibit a seasonal variation. Stroke in AF patients is common and often severe. Obtaining a description of a possible seasonal variation in the occurrence of stroke in AF patients is crucial in clarifying risk factors for developing stroke and initiating prophylaxis treatment.
methodsUsing a dynamic generalized linear model we were able to model gradually changing seasonal variation in hospitalization rates of stroke in AF patients from 1977 to 2011. The study population consisted of all Danes registered with a diagnosis of AF comprising 270,017 subjects. During follow-up, 39,632 subjects were hospitalized with stroke. Incidence rates of stroke in AF patients were analyzed assuming the seasonal variation being a sum of two sinusoids and a local linear trend.
resultsThe results showed that the peak-to-trough ratio decreased from 1.25 to 1.16 during the study period, and that the times of year for peak and trough changed slightly.
conclusionThe present study indicates that using dynamic generalized linear models provides a flexible modeling approach for studying changes in seasonal variation of stroke in AF patients and yields plausible results.
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